Tracking and data association
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
3D articulated models and multiview tracking with physical forces
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
3-D model-based tracking of humans in action: a multi-view approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Sequential Monte Carlo Tracking of Body Parameters in a Sub-Space
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Advances in view-invariant human motion analysis: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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In this paper we present a system for human body model acquisition and tracking of its parameters from voxel data. 3D voxel reconstruction of the body in each frame is computed from silhouettes extracted from multiple cameras. The system performs automatic model acquisition using a template based initialization procedure and a Bayesian network for refinement of body part size estimates. The twist-based human body model leads to a simple formulation of the extended Kalman filter that performs the tracking and with joint angle limits guarantees physically valid posture estimates. Evaluation of the approach was performed on several sequences with different types of motion captured with six cameras.